Next, we run the margins command to get the six adjust cell means from the 3x2
interaction. These adjusted cells means are called least squares means (lsmeans) in SAS or estimated marginal
means (emmeans) in SPSS.

We will use the margins command to get the predicted probabilities for 11 values of
s from 20 to 70 for both f equal zero and f equal one. The vsquish
option just reduces the number of blank lines in the output.

In total, there are 22 values in the above table. There are two predicted probabilities for each value of
s. One each for males and females.

Now we can go ahead and graph the probabilities
using the marginsplot command. This time we will include the default confidence intervals.

marginsplot

We can make the graph more visually attractive by shading the area inside the confidence intervals.

marginsplot, recast(line) recastci(rarea)

The graph of the probabilities above is nice as far as it goes but the presentation of the results
might be clearer if we were to graph the difference in probabilities between males and females.
To do this we will need to rerun the margins command computing
the discrete change for f at each value of read. We can get the difference using the
dydx (derivative) option.